Optimizing Engagement in Digital Mental Health Services among Sexual and Gender Minority Consumers

项目摘要 性和性别少数群体（SGM）受心理健康问题的影响不成比例 相对于他们的异性恋和顺性别同龄人。然而，SGM人群继续报告未满足的心理需求， 健康需求，因为他们无法或无法获得心理健康服务。数字心理健康（DMH） 被认为是一种可行的，经济的，有效的方法，以扩大精神卫生的可用性 关心那些面临心理健康求助障碍的消费者。SGM消费者对DMH的偏好 资源，这种交付形式有望解决这一领域所遇到的主要访问障碍。 消费者群体。然而，根据SGM消费者的需求定制的DMH内容的可用性是有限的， 缺乏研究检查SGM人群的实际参与DMH服务。的潜在解决方案 充分了解SGM人群如何利用DMH服务将是描述他们在一个 自然环境利用与美国心理健康协会（MHA）建立的伙伴关系， 健康倡导小组提供免费的，基于证据的筛查和自我指导的DMH资源，这项研究将 跟踪SGM DMH消费者的大规模自然样本，目的是：1）描述消费者的电流 与MHA的DMH资源互动的预测模式，并研究消费者特征 与这些不同的参与模式相关（目标1）; 2）采用以人为本的设计方法， 获得与影响DMH的MHA元数据未捕获的特定于组的过程相关的见解 SGM消费者之间的互动，并整合数据以设计和构建原型互动策略 用于消费者评估（目标2），以及; 3）与MHA的SGM消费者一起测试定制的参与策略 使用微随机试验（MRT）设计（目标3）。为了实现这些目标，并为更大的R 01做好准备 在试验中，主要研究者将接受以下方面的培训：1）理论、实质性和方法学 DMH的基础; 2）大数据管理和分析方法，特别是监督机器学习; 3)以人为本的设计方法，用于设计定制的DMH干预措施，以及; 4）实验设计 和数据分析，以评估适应DMH干预措施。候选人是社会学助理教授 在华盛顿大学工作，其长期职业目标是成为心理学领域的专家。 卫生服务研究，专门从事数字干预，以改善SGM消费者的服务获取 通过增加可用性和提高可接受性。拟议的研究通过以下方式推进了这一目标： 与SGM消费者的护理偏好保持一致，利用现有DMH平台的基础设施 以最小的消费者负担，并为SGM的优化参与结果提供证据 消费者通过使用定制的策略。

PROJECT SUMMARY Sexual and gender minority (SGM) populations are disproportionately impacted by mental health concerns relative to their heterosexual and cisgender peers. SGM populations, however, continue to report unmet mental health needs because they cannot or do not access mental health services. Digital Mental Health (DMH) has been recognized as a feasible, economical, and effective approach to broaden the availability of mental health care to consumers who face barriers to mental health help-seeking. SGM consumers cite a preference for DMH resources, and this delivery format holds promise to attend to major access barriers experienced by this consumer group. Yet, the availability of DMH content tailored to the needs of SGM consumers is limited, and a dearth of research examines SGM populations' actual engagement with DMH services. A potential solution to fully understand how SGM populations utilize DMH services would be to characterize their engagement within a natural setting. Leveraging an established partnership with Mental Health America (MHA), a non-profit mental health advocacy group offering free, evidence-based screenings and self-guided DMH resources, this study will follow a large, naturalistic sample of SGM DMH consumers with the aims to: 1) characterize consumers' current and predictive patterns of engagement with MHA's DMH resources and examine consumer characteristics associated with these different engagement patterns (Aim 1); 2) employ human-centered design approaches to gain insights related to group-specific processes not captured by MHA's meta-data that impact DMH engagement among SGM consumers and integrate data to design and build prototype engagement strategies for consumer evaluation (Aim 2), and; 3) test the tailored engagement strategies with MHA's SGM consumers using a micro-randomized trial (MRT) design (Aim 3). To accomplish these aims and prepare for a larger R01 trial, the Principal Investigator will receive training in: 1) the theoretical, substantive, and methodological underpinnings of DMH; 2) big data management and analytic methods, specifically supervised machine learning; 3) human-centered design approaches for designing tailored DMH interventions, and; 4) experimental design and data analysis for evaluating adaptive DMH interventions. The candidate is an Assistant Professor of Social Work at the University of Washington whose long-term career goal is to become an expert in the field of mental health services research, specializing in digital interventions to improve service access for SGM consumers through increased availability and enhanced acceptability. The proposed study advances this objective by aligning with the care preferences of SGM consumers, leveraging the infrastructure of an existing DMH platform at minimal burden to consumers, and contributing evidence towards optimized engagement outcomes for SGM consumers through the use of tailored strategies.